Crisp dm

7 important questions on Crisp dm

Which phases are there in the crisp dm model?

  • Business understanding
  • Data understanding
  • data preparation
  • modeling
  • evaluation
  • deployment

What are the characteristics of the business understanding phase?

  • This is the phase where you want to understand the question the client has for you
  • to do this you want to have an understanding of what their company is like: company culture, mission, strategy
  • You want to become aware of stakeholders: who has interest in this project, and who do i need to keep happy the most?
  • you want to translate your business problem to a data science problem
  • the goals of this phase are accomplished by having a client interview

What are the characteristics of the data understanding phase

  • In this phase you want to explore what data is available to you and how it can be used to answer the question of the client
  • steps in this phase can be:
    • data acquiring
    • data exploring
    • verifying data quality
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What are characteristics of the data preparation phase?

  • In the data preparation phase you'll reshape your data to make it fit for modelling
  • steps in this phase can be:
    • Joining datasets
    • selecting variables
    • data cleaning
    • feature extraction
    • formatting data

What are some characteristics of the modeling phase?

  • In the modeling phase you built and evaluate different models to answer your question
  • ensure that you employ models that the client is comfortable with: start out simple and only use more complex models if you have to.
  • client satisfaction is most important so with every increase in model complexity the client satisfaction may decrease

What are characteristics of the evaluation phase?

  • In the evaluation phase you review whether the results from the modeling phase satisfy the client
    • determine whether they understand what you did an are happy with the modeling result

What are characteristics of the deployment phase?

  • In this phase your data analysis gets translated back to the business level
  • the entire process is described and modeling results are transformed to an agreed upon finish product like an advise or a dashboard.

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